A Robust Observation, Planning, and Control Pipeline for Autonomous Rendezvous with Tumbling Targets - Albee, Keenan; Oestreich, Charles; Specht, Caroline; Terán Espinoza, Antonio; Todd, Jessica; Hokaj, Ian; Lampariello, Roberto; Linares, Richard (Frontiers in Robotics and AI, 2021)
A growing number of retired satellites, particularly in higher orbits like geostationary orbit, remain nearly functional except for minor but critical malfunctions or fuel depletion. Servicing these ailing satellites and cleaning up “high-value” space debris remains a formidable challenge, but active interception of these targets with autonomous repair and deorbit spacecraft is inching closer toward reality as shown through a variety of rendezvous demonstration missions. However, some practical challenges are still unsolved and undemonstrated. Devoid of station-keeping ability, space debris and fuel-depleted satellites often enter uncontrolled tumbles on-orbit. In order to perform on-orbit servicing or active debris removal, docking spacecraft (the “Chaser”) must account for the tumbling motion of these targets (the “Target”), which is oftentimes not known a priori. Accounting for the tumbling dynamics of the Target, the Chaser spacecraft must have an algorithmic approach to identifying the Target’s tumble and using this information to produce useful motion planning and control. This work addresses the entire pipeline of rendezvous with such a Target, starting from a standoff estimation point to a mating point fixed in the rotating Target’s body frame while considering the uncertainty contribution of online Target estimation. A novel visual estimation algorithm is applied using a 3D time-of-flight camera to perform remote standoff estimation of the Target’s rotational state and the accompanying covariance. An nonlinear programming-based motion planning algorithm is employed, making use of offline simulation of potential Target tumble types to produce a look-up table that is parsed on-orbit using the estimation data to produce a Target body frame reference trajectory online. Finally, an uncertainty bound is generated accounting for imperfect Target estimation and is provided to a robust tube model predictive controller, which provides tube-based robustness guarantees on the system’s ability to follow the reference trajectory translationally. Detailed simulation results of the complete pipeline are presented as a whole with individual performance metrics, showing its applicability as the work prepares to move toward ground and ISS demonstration.